Stroke is the third leading cause of death in the United States and treatment options are limited. Clinical trials of neuroprotective agents have failed to show efficacy and it is believed that this failure is due to the inability to administer neuroprotective agents quickly enough to rescue ischemic brain. We need to develop therapies to reduce ischemic injury and extend the therapeutic window for neuroprotection. We describe exciting preliminary data we have obtained in a rat cerebral ischemia model suggesting that thiazolidinediones (TZDs), a class of drugs, already FDA approved for use in type 2 diabetes and currently under study as a secondary preventative agent for stroke, is neuroprotective. Importantly, we find that TZDs must be administered prior to reperfusion in order to be effective. These drugs are effective when administered up to three hours after occlusion, and treatment is beneficial, even if it causes a delay in reperfusion. Preliminary data to date utilize an intraperitoneal administration which is not suitable for use in humans. These studies aim to clarify the efficacy IV TZD administration, define optimal dose and the window of efficacy both related to time of ischemia and reperfusion. We also propose to examine serum levels of free fatty acids which increase in response to TZDs and soluble intercellular adhesion molecule (ICAM) and matrix metalloproteinase (MMP)-9, which may serve as biomarkers of TZD mediated efficacy and may aid in the translation of this work to humans. In addition the efficacy of TZDs is confirmed in female rats which may more closely represent the human population subject to stroke. PUBLIC HEALTH RELEVANCE: Stroke is a devastating disease with limited treatment options. While thiazolidinediones are already FDA approved for the treatment of type 2 diabetes, we have found that they are effective in reducing injury and improving neurologic function in an animal model. We propose studies aimed at defining optimal dosing paradigms in rodents with the eventual aim of translating these data to human trails.